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Research on the Optimum Water Content of Detecting Soil Nitrogen Using Near Infrared Sensor

机译:近红外传感器检测土壤氮素的最佳含水量研究

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摘要

Nitrogen is one of the important indexes to evaluate the physiological and biochemical properties of soil. The level of soil nitrogen content influences the nutrient levels of crops directly. The near infrared sensor can be used to detect the soil nitrogen content rapidly, nondestructively, and conveniently. In order to investigate the effect of the different soil water content on soil nitrogen detection by near infrared sensor, the soil samples were dealt with different drying times and the corresponding water content was measured. The drying time was set from 1 h to 8 h, and every 1 h 90 samples (each nitrogen concentration of 10 samples) were detected. The spectral information of samples was obtained by near infrared sensor, meanwhile, the soil water content was calculated every 1 h. The prediction model of soil nitrogen content was established by two linear modeling methods, including partial least squares (PLS) and uninformative variable elimination (UVE). The experiment shows that the soil has the highest detection accuracy when the drying time is 3 h and the corresponding soil water content is 1.03%. The correlation coefficients of the calibration set are 0.9721 and 0.9656, and the correlation coefficients of the prediction set are 0.9712 and 0.9682, respectively. The prediction accuracy of both models is high, while the prediction effect of PLS model is better and more stable. The results indicate that the soil water content at 1.03% has the minimum influence on the detection of soil nitrogen content using a near infrared sensor while the detection accuracy is the highest and the time cost is the lowest, which is of great significance to develop a portable apparatus detecting nitrogen in the field accurately and rapidly.
机译:氮是评价土壤生理生化特性的重要指标之一。土壤氮含量水平直接影响农作物的营养水平。近红外传感器可用于快速,无损且方便地检测土壤中的氮含量。为了研究不同水分含量对近红外传感器检测土壤氮素的影响,对土壤样品进行了不同的干燥时间处理,并测定了相应的水分含量。干燥时间设置为1小时至8小时,每1小时检测90个样品(每个氮气浓度为10个样品)。利用近红外传感器获得样品的光谱信息,同时每1 h计算一次土壤含水量。通过两种线性建模方法建立了土壤氮含量的预测模型,包括偏最小二乘(PLS)和无信息变量消除(UVE)。实验表明,干燥时间为3 h,土壤含水量为1.03%时,土壤的检测精度最高。校准集的相关系数分别为0.9721和0.9656,预测集的相关系数分别为0.9712和0.9682。两种模型的预测精度都很高,而PLS模型的预测效果更好,更稳定。结果表明,土壤水含量为1.03%对使用近红外传感器检测土壤氮含量的影响最小,而检测精度最高,时间成本最低,这对于开发一种土壤水分检测方法具有重要意义。便携式设备,可在野外准确,快速地检测氮。

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